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Capturing relevant information from the body of emails sent to a process model
John Stretton
over 7 years ago
I'm trying to create a feature to allow users to communicate by email and have their communication tracked by Appian and stored in a database. However, I'm having a hard time capturing the meaningful information from the body of the email message. Email signatures and the content of emails earlier in the chain are also captured. Has anyone implemented a solution that does what I'm trying to accomplish?
For example, I tried sending an email with just the word "Testing" in the body, but striphtml(msg!body) returns all of this garbage, including my email signature:
Testing________________________________[cid:image001.jpg@01CC47C6.5B839AF0]John StrettonEDP Renewables North AmericaCorporate InitiativesAddress here, Houston, TX 77002Direct xxx.xxx.xxxxwww.edpr.comTake action. Use energy efficient products.This e-mail is for the use of the intended recipient(s) only. If y...
OriginalPostID-257049
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John Stretton
over 2 years ago
in reply to
mmniloban
+1
suggested
Here's my approach. You'll need to install the Email Reply Parser plugin first and you will also need the Appian Regular Expression Functions plugin. You can replace the hard-coded search strings with…
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ashokv
A Score Level 1
over 7 years ago
@johns222: For our process, we have extracted various details of the email using the functions like property(msg!properties,"Subject","Not Available")--pv!subject_txt, msg!body--pv!emailBody_txt in the 'receive message event'. Then we have saved these details into CDT and save into DB. From these, we extracted various details using combination of striphtml() and extract() functions. Hope this helps.
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ashokv
A Score Level 1
over 7 years ago
@johns222: For our process, we have extracted various details of the email using the functions like property(msg!properties,"Subject","Not Available")--pv!subject_txt, msg!body--pv!emailBody_txt in the 'receive message event'. Then we have saved these details into CDT and save into DB. From these, we extracted various details using combination of striphtml() and extract() functions. Hope this helps.
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